Top AI & Machine Learning Jobs

Design, build, and deploy AI-powered conversational voice solutions using LLMs and cloud services. Integrate and fine-tune models, architect scalable real-time voice APIs, optimize bot performance, and collaborate cross-functionally to deliver responsible generative AI agents.

The Director will define AI strategies, lead development of AI agents, drive engineering enablement, and ensure solutions meet business objectives while aligning with enterprise standards.

Build and productionize generative AI and classical ML solutions for healthcare: data preparation, feature engineering, model/prompt development, evaluation, deployment, MLOps, monitoring, retrieval/indexing, and responsible AI practices while collaborating with cross-functional stakeholders.

Lead business analysis and governance for an Agentic AI portfolio in claims operations. Standardize requirements, translate claims logic into AI rules and prompts, manage cross-functional delivery, implement AI rule libraries, ensure compliance and audit readiness, and track value realization across adjudication, payment integrity, and rework automation.

Lead design and delivery of AI-enabled enterprise applications: integrate and operationalize LLMs and Generative AI, build APIs/microservices, implement RAG/vector DB solutions, ensure responsible AI and MLOps, mentor engineers, drive CI/CD and observability, and collaborate with cross-functional teams to deploy reliable, secure AI services.

Lead design and delivery of CI/CD pipelines, cloud IaC (Terraform), containerization, and DevSecOps. Build scalable microservices and web apps using TypeScript/React and Python with SQL backends. Design, integrate, and deploy AI solutions (LLMs, RAG, vector DBs, conversational and agentic AI). Mentor engineers, drive reliability, security, automation, and improve developer experience.

Lead analytics for Medicaid quality programs: build analytical frameworks, perform data analyses and causal inference to evaluate program impact, translate requirements into scalable data models, collaborate with cross-functional teams, and communicate findings and risks to stakeholders to drive quality improvements.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.

Lead research and development of LLM and generative AI solutions, design scalable real-time ML models, define priorities and metrics for deep learning and RAG, promote Responsible AI best practices, and drive adoption of new methods across teams.

Design and implement AI/ML systems for healthcare, own inference and delivery, manage/scale production ML systems, build scalable data pipelines and APIs, apply MLOps practices (deployment, monitoring, drift detection), and work with large-scale data and distributed computing frameworks.